Classified Raster Map Analysis for Sustainable Environment and Development in the 21st Century: A Perspective

نویسنده

  • G. P. Patil
چکیده

Geospatial data form the foundation of an information-based society. Cell-based raster data are well suited to represent geographic phenomena and help model landcover and landuse characteristics and relevant attributes. Information technologies capable of credible raster map analysis and change detection are needed for integrated regional assessment and development in the 21st Century equipped with remote sensing and other geospatial data. The paper discusses examples of ecosystem health assessment at landscape and watershed scales using relatively new concepts and measures of landscape fragmentation. The methods include hierarchical transition matrix analysis, fragmentation profile analysis, echelon analysis, and nested area sampling analysis.

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تاریخ انتشار 2000